Using a pattern-based ESE (a.k.a., seed set expansion) technique on top of AL helped our approach in discovering rare patterns and rules which might have been hidden when using only a feature-based system [1]}. Our ESE method is similar to [2]}, [3]}, [4]} where the system starts with a few positive examples of an entity class and tries to extract similar entities. Additionally, we use a richer set of features than those in [5]}, [6]}, [7]} while training a CRF model and using it to further find positive examples of a given entity class.
